Teaching and training can be difficult and time-consuming. Good teachers and instructors are usually in scarce supply and high student to teacher/instructor ratios prevent individualized instruction and thus are a barrier to deep learning. Tools to make each teacher/instructor more effective are desirable, as they can decrease the number of teachers/instructors required. These tools are especially valuable if they can also improve the quality of the education given to students, who are constantly pushed to learn more and do to learn it faster because of the ever-increasing economic demand for education/training.
The information that a learner acquires from a graphical interface is often measured by learning outcomes, or other indirect metrics. Eye-tracking offers a direct metric that can measure what the user attended to, i.e., read/viewed on the screen.
Visual displays, diagrams, and simulations are now widely used as information sources for learning in the media in order to convey important information, and at all levels of education for learning, rich problem-solving, and diagnosis (e.g., science, mathematics, electrical engineering, radiology, airport security, airplane navigation). Despite the proliferation of visual materials and the important role they play in knowledge dissemination and knowledge acquisition, surprisingly little is known about how information from visual information sources is acquired, or how their comprehension can be improved.
One of the principal complex issues with visual information sources is that they provide all information simultaneously; in direct contrast to more conventionally-used textual information sources which are structured sequentially. The implications of this are that the knowledge acquisition processes and comprehension processing of textual information follows the structure of the text (from the first word in the paragraph to the last). In the case of visual information sources, however, the processing of information is directed by the learner, that is, his/her attentional processes are guided in a systematic (or unsystematic) fashion to acquire the relevant information to complete the task at hand. It is known that prior domain knowledge is highly predictive of a user's visual search patterns and knowledge acquisition processes. For example, experts in architecture search through each 2-dimensional plan to best understand the 3-dimensional nature of the building, and medical experts systematically seek information in an x-ray to either confirm or disconfirm a diagnosis.
In the case of science learning, the underlying causal structure must be understood from the diagram; since all information is presented simultaneously, this, in the absence of prior knowledge, is a highly complex task. It was once believed that simply adding a diagram as an accompaniment to a text would improve learner's understanding; however, research has shown that novices do not know what is salient in the diagram, and in the case of highly conventionalized diagrams (e.g., topographical maps, VLSI diagrams, architectural maps, etc.), novices are not fluent enough with the symbol system to permit easy comprehension.